{"id":"W2024233572","doi":"10.1016/j.spl.2010.05.015","title":"Bootstrap procedures for the pseudo empirical likelihood method in sample surveys","year":2010,"lang":"en","type":"article","venue":"Statistics & Probability Letters","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Empirical likelihood; Statistics; Mathematics; Confidence interval; Sample size determination; Statistic; Coverage probability; CDF-based nonparametric confidence interval; Sampling design; Sampling (signal processing); Variance (accounting); Benchmark (surveying); Population; Econometrics; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006090257,0.000310352,0.0004781891,0.00006899564,0.0002030059,0.0001240544,0.0004834466,0.0001483686,0.0002398369],"category_scores_gemma":[0.03807683,0.0002202345,0.0001034969,0.0002636435,0.0003999881,0.00006895384,0.00008450202,0.0007137443,0.000006085435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006254255,"about_ca_system_score_gemma":0.000229908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002679919,"about_ca_topic_score_gemma":0.003279906,"domain_scores_codex":[0.9966804,0.0008944023,0.0007550736,0.0006089763,0.000374832,0.0006863427],"domain_scores_gemma":[0.9620175,0.03678253,0.0001759157,0.0006741458,0.0001986703,0.0001511738],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005899624,0.0003057007,0.01526951,0.0005753145,0.00004540411,0.000005672705,0.0006791924,0.000001088669,0.001976149,0.8909292,0.01007519,0.08007859],"study_design_scores_gemma":[0.0004327794,0.0000810479,0.04572769,0.00002121419,0.00006219042,0.000006761925,0.00001394434,0.0022317,0.0002129278,0.950503,0.0004277262,0.0002790617],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009545167,0.000005661326,0.9824128,0.004455498,0.0003692954,0.001538888,0.001548222,0.0000697631,0.00005466937],"genre_scores_gemma":[0.01079961,0.000002388527,0.9875356,0.001031171,0.0001433366,0.0004103356,0.00002945563,0.00004187539,0.000006222808],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.07979953,"threshold_uncertainty_score":0.9700258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09791854182274352,"score_gpt":0.4215707332005172,"score_spread":0.3236521913777737,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}